Ferry Electrification Energy Demand and Particle Swarm Optimization Charging Scheduling Model Parameters Analysis by Tomislav Peša, Maja Krčum, Grgo Kero, Joško Šoda

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A new hybrid distance and similarity based scenario reduction approach for stochastic economic operation of microgrid by Gaurav Gangil, Amit Saraswat, Sunil Kumar Goyal

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FRB Line-of-sight Ionization Measurement from Lightcone AAOmega Mapping Survey: The First Data Release by Yuxin Huang, Sunil Simha, Ilya S. Khrykin, Khee-Gan Lee, J. Xavier Prochaska, Nicolas Tejos, Keith W. Bannister, Jason Barrios, John Chisholm, Jeff Cooke, Adam T. Deller, Marcin Glowacki, Lachlan Marnoch, R. M. Shannon, Jielai Zhang

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Multi-objective optimization models for power load balancing in distributed energy systems by Zhuo Wang, Yuchen Luo, Wei Wu, Lei Cao, Zhun Li

“…Uncertainty and several competing criteria on the demand and generation sides make multi-objective optimization difficult. Selecting a model capable of resolving scheduling issues related to loads and dispersed energy sources is, therefore, essential. …”
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Regional-Scale Energy Modelling for Developing Strategies to Achieve Climate Neutrality by Janusz Zyśk, Artur Wyrwa, Maciej Raczyński, Marcin Pluta, Wojciech Suwała

“…In the framework of analysis, the 3E (Energy–Economy–Environment) class optimisation model was developed. The objective function includes the costs of energy in the medium and long term. …”
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Remote Sensing Extraction of Damaged Buildings in the Shigatse Earthquake, 2025: A Hybrid YOLO-E and SAM2 Approach by Zhimin Wu, Chenyao Qu, Wei Wang, Zelang Miao, Huihui Feng

“…The dataset used for training contained labeled examples of damaged buildings, and the model optimization was carried out using stochastic gradient descent (SGD), with cross-entropy and mean squared error as the selected loss functions. Upon evaluation, the model reached a precision of 0.840, a recall of 0.855, an F1-score of 0.847, and an IoU of 0.735. …”
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Benchmarking reinforcement learning and accurate modeling of ground source heat pump systems: Intelligent strategy using spiking recurrent neural network combined with spider WASP... by Sana Qaiyum, Kashif Irshad, Mohamed E. Zayed, Salem Algarni, Talal Alqahtani, Asif Irshad Khan

“…Furthermore, the proposed SWO-SRNN was trained using the selected features to predict the ground temperature and Coefficient of Performance (COP), which enables to make appropriate actions to optimize the functioning of GSHP. …”
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Continuous-Variable Quantum Key Distribution Protocol Based on Post-Selection by Hao YU, Bao FENG, Zichun PAN, Wenhe ZHUO, Zhenwei LI

“…In the paper, we present a CVQKD protocol based on post-selection method, which need not any extra single photon source. …”
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Integrating green hydrogen storage into mine water pumping stations in the context of energy transition by Andrzej Chmiela, Beata Barszczowska, Pedro Riesgo Fernandez, Marcin Lutyński, Ronghou Liu, Le Zhang, Natalia Howaniec, Łukasz Hankus, Adam Smoliński

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Forecasting Electricity Production in a Small Hydropower Plant (SHP) Using Artificial Intelligence (AI) by Dawid Maciejewski, Krzysztof Mudryk, Maciej Sporysz

“…This article devises the Artificial Intelligence (AI) methods of designing models of short-term forecasting (in 12 h and 24 h horizons) of electricity production in a selected Small Hydropower Plant (SHP). Renewable Energy Sources (RESs) are difficult to predict due to weather variability. …”
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The Relationship Between Soil and Gut Microbiota Influences the Adaptive Strategies of Goitered Gazelles in the Qaidam Basin by Yiran Wang, Bin Li, Bo Xu, Wen Qin

“…Interactions with soil microbiota can shape the composition and function of the gut microbiota, thereby influencing the hosts’ adaptive strategies. …”
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An Attomolar-Level Optical Device for Monitoring Receptor–Analyte Interactions Without Functionalization Steps: A Case Study of Cytokine Detection by Nunzio Cennamo, Francesco Arcadio, Chiara Marzano, Rosalba Pitruzzella, Mimimorena Seggio, Maria Pesavento, Stefano Toldo, Antonio Abbate, Luigi Zeni

“…The POF-based device was proven to be effective for detecting several interleukins at the attomolar level in a few minutes and without functionalization processes.…”
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Source Type Recognition Algorithm of Radio Emission using Radial Basis Functions by V. F. Korotkov, R. S. Zyryanov

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An enhancement filter utilizing the modified arctangent function for the structural and tectonic interpretation of causative sources: Application to WGM2012 gravity data from the R... by Fengjun WU, Xin-Ai XU

“…In this study, we propose the Modified Arctangent Function (MAT), which enhances gravity source edge detection by integrating the total horizontal gradient with a modified arctangent function. …”
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Ecological processes influencing bacterial community assembly across plant niche compartments by Nazish Roy, Seongeun Yang, Dongmin Lee, Kihyuck Choi

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Source Detection and Functional Connectivity of the Sensorimotor Cortex during Actual and Imaginary Limb Movement: A Preliminary Study on the Implementation of eConnectome in Motor Imagery Protocols by Alkinoos Athanasiou, Chrysa Lithari, Konstantina Kalogianni, Manousos A. Klados, Panagiotis D. Bamidis

“…Event-Related Desynchronization/Synchronization (ERD/ERS) of the mu-rhythm was used to evaluate MI performance. Source detection and FCNs were studied with eConnectome. …”
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Feature dependence graph based source code loophole detection method by Hongyu YANG, Haiyun YANG, Liang ZHANG, Xiang CHENG

“…Given the problem that the existing source code loophole detection methods did not explicitly maintain the semantic information related to the loophole in the source code, which led to the difficulty of feature extraction of loo-phole statements and the high false positive rate of loophole detection, a source code loophole detection method based on feature dependency graph was proposed.First, extracted the candidate loophole statements in the function slice, and gen-erated the feature dependency graph by analyzing the control dependency chain and data dependency chain of the candi-date loophole statements.Secondly, the word vector model was used to generate the initial node representation vector of the feature dependency graph.Finally, a loophole detection neural network oriented to feature dependence graph was constructed, in which the graph learning network learned the heterogeneous neighbor node information of the feature de-pendency graph and the detection network extracted global features and performed loophole detection.The experimental results show that the recall rate and F1 score of the proposed method are improved by 1.50%～22.32% and 1.86%～16.69% respectively, which is superior to the existing method.…”
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Feature dependence graph based source code loophole detection method by Hongyu YANG, Haiyun YANG, Liang ZHANG, Xiang CHENG

“…Given the problem that the existing source code loophole detection methods did not explicitly maintain the semantic information related to the loophole in the source code, which led to the difficulty of feature extraction of loo-phole statements and the high false positive rate of loophole detection, a source code loophole detection method based on feature dependency graph was proposed.First, extracted the candidate loophole statements in the function slice, and gen-erated the feature dependency graph by analyzing the control dependency chain and data dependency chain of the candi-date loophole statements.Secondly, the word vector model was used to generate the initial node representation vector of the feature dependency graph.Finally, a loophole detection neural network oriented to feature dependence graph was constructed, in which the graph learning network learned the heterogeneous neighbor node information of the feature de-pendency graph and the detection network extracted global features and performed loophole detection.The experimental results show that the recall rate and F1 score of the proposed method are improved by 1.50%～22.32% and 1.86%～16.69% respectively, which is superior to the existing method.…”
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Spin-dependent edge detection and imaging enabled by optical circularly polarised states by Jiale Chen, Zhao-xian Chen, Zi-xin Zhou, Yan-qing Lu, Jun-long Kou

“…By harnessing the chiral selectivity of the C-points, a high-CD PCS imager can provide two sets of optical transfer functions (OTFs) to facilitate both edge detection and bright-field imaging. …”
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Selenium Accumulating Leafy Vegetables Are a Potential Source of Functional Foods by Petro E. Mabeyo, Mkabwa L. K. Manoko, Amra Gruhonjic, Paul A. Fitzpatrick, Göran Landberg, Máté Erdélyi, Stephen S. Nyandoro

“…., Cucurbita maxima, Ipomoea batatas, Solanum villosum, Solanum scabrum, and Vigna unguiculata were explored for their capabilities to accumulate selenium when grown on selenium enriched soil and for use as a potential source of selenium enriched functional foods. Their selenium contents were determined by spectrophotometry using the complex of 3,3′-diaminobenzidine hydrochloride (DABH) as a chromogen. …”
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